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Analysis and modeling of heat-labile enterotoxins of Escherichia coli suggests a novel space with insights into receptor preference a
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M. Krishna Raja , Asit Ranjan Ghosh , S. Vino & S. Sajitha Lulu
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School of Bio Sciences and Technology, VIT University, Vellore, India Published online: 06 Nov 2014.
Click for updates To cite this article: M. Krishna Raja, Asit Ranjan Ghosh, S. Vino & S. Sajitha Lulu (2014): Analysis and modeling of heatlabile enterotoxins of Escherichia coli suggests a novel space with insights into receptor preference, Journal of Biomolecular Structure and Dynamics, DOI: 10.1080/07391102.2014.974073 To link to this article: http://dx.doi.org/10.1080/07391102.2014.974073
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Journal of Biomolecular Structure and Dynamics, 2014 http://dx.doi.org/10.1080/07391102.2014.974073
Analysis and modeling of heat-labile enterotoxins of Escherichia coli suggests a novel space with insights into receptor preference M. Krishna Raja, Asit Ranjan Ghosh, S. Vino and S. Sajitha Lulu* School of Bio Sciences and Technology, VIT University, Vellore, India Communicated by Ramaswamy H. Sarma
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(Received 20 January 2014; accepted 4 October 2014) Features of heat-labile enterotoxins of Escherichia coli which make them fit to use as novel receptors for antidiarrheals are not completely explored. Data-set of 14 different serovars of enterotoxigenic Escherichia coli producing heat-labile toxins were taken from NCBI Genbank database and used in the study. Sequence analysis showed mutations in different subunits and also at their interface residues. As these toxins lack crystallography structures, homology modeling using Modeller 9.11 led to the structural approximation for the E. coli producing heat-labile toxins. Interaction of modeled toxin subunits with proanthocyanidin, an antidiarrheal showed several strong hydrogen bonding interactions at the cost of minimized energy. The hits were subsequently characterized by molecular dynamics simulation studies to monitor their binding stabilities. This study looks into novel space where the ligand can choose the receptor preference not as a whole but as an individual subunit. Mutation at interface residues and interaction among subunits along with the binding of ligand to individual subunits would help to design a non-toxic labile toxin and also to improve the therapeutics. Keywords: receptor; labile toxin; interface residue; mutation
1. Introduction Enterotoxigenic Escherichia coli (ETEC) play a critical role in causing diarrheal-related illness among mammals (Levine, 1987). It causes travelers’ diarrhea mainly in the developing world (Wang et al., 2010) and also causes diarrhea in infants, children, and adults leading to global health problem. It emphasizes the need to understand and analyze the role of ETEC toxin genes in humans which has a heterohexamer (AB5) complex consisting of catalytically active monomeric A subunit (LTA) and pentameric B subunits (LTB) (Merritt & Hol, 1995). Heat-labile (LT) enterotoxin is one of the essential components in disease pathogenesis resulting in gut lumen dehydration (Nataro & Kaper, 1998). In addition to pathogenicity expression of LT, colonization is an added advantage (Allen, Randolph, & Fleckenstein, 2006; Berberov et al., 2004). Vaccine development is facing hurdles due to the variability of antigens among strains (Svennerholm & Tobias, 2008). It is well documented that the mutation has an impact on toxicity, adjuvant activity, cytotonic effect, cAMP levels, and ADP ribosylation (Rodrigues et al., 2011). Significance of mutation can be deciphered from reports like mutation in cysteine residues which results in degradation of LTA by proteases and thereby reduction in cAMP production (Okamoto, Nomura, Fujii, & Yamanaka, 1998). *Corresponding author. Email: [email protected] © 2014 Taylor & Francis
Therefore, the present study enumerates the necessity of analyzing the subunit sequence for mutation, interface residues, and interaction of ligands with individual subunits which would be useful for developing drugs for treatment and prevention. 2. Methods 2.1. LT data-set Complete sequences of heat-labile enterotoxin (LT) of E. coli were taken from the Genbank database. Among the several hits found, the complete sequences were selected from both the A and B subunit toxin. As illustrated in Figure 1, using keyword search in Genbank database, the respective hits 14 for LTA and 71 for LTB were obtained as search results (Table 1). For LTA, the 14 hits representing E. coli were selected, while for LTB the first 14 hits for full length sequence were selected for the data-set. 2.2. Multiple sequence alignment of LTA and LTB Multiple sequence alignment (MSA) was performed using clustalW2 protein with the substitution matrix PAM, extension penalty of .20, and gap-opening penalty of 10. 1LTS available in the Brookhaven protein data bank (PDB) database (Abola, Bernstein, & Koetzle,
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Figure 1.
Creation of sequence data-set for E. coli labile toxins, LTA and LTB.
Table 1. Data-set summary for LTA and LTB sequences from various serotypes. Number of sequences Strain 2781–5 61A-4 63-V PE0615 4321–1 4692–1 214-III 4702–1 PE0415 PE0534 225-IV 121-I 1372–1 136-I Total
Serotype
LTA
LTB
O78:H12 O78:H12 O159:H17 ONT:H9 ONT:HONT:HONT:HNT O167:H5 O152:H2 O106:H40 O148:H28 O48:H21 O23:H28 O88:H25
1 1 1 1 1 1 1 1 1 1 1 1 1 1 14
1 1 1 1 1 1 1 1 1 1 1 1 1 1 14
1984) is used as the reference sequence in this study. The alignment was done to predict mutation in the toxin. The mutations were further analyzed to locate their presence in the interface residue positions, as they are vital in forming the structural assembly and in deciding the functional role. For mutations corresponding to the gaps of the reference sequence, the amino acid which appears most is taken as reference. 2.3. Interface residues Interface residues were determined by calculating the change in solvent-accessible surface area by prosurf
[http://curie.utmb.edu] and in the interacting residues by protInDB [http://protindb.cs.iastate.edu/]. The interface residues and their mutations are given in MSA. Among the interface residues identified in the different subunits of the toxin, the interface residues between the A and the B5 subunit and one representative of the D monomer from the entire B subunit were taken into account. In the B subunit, the interface residues occur between the two adjacent monomers. D monomer has its adjacent interface interactions with E and H monomers. As they are five monomers, analyzing one of the monomers properties implies the rest. 2.4. Molecular modeling There is no X-ray crystallographic structure for the set of sequences in the data-set. Template for modeling was chosen by the maximum identity and statistical E measure of the query sequence with the PDB database (Abola et al., 1984) by using blast algorithm. Threedimensional homology models were constructed for target proteins using LT crystal structures with PDB ID: 1LTA and 1LTB for A and B chains, respectively. Sequences of subunit A, C (part of subunit A) and B were modeled using MODELLER version 9.11 (Fiser & Šali, 2003). Out of five modeled proteins for each sequence, the best one was selected based on the DOPE score. Homology modeled proteins were energy minimized after adding hydrogen atoms and conformation of the models was evaluated using procheck by visualizing the Ramachandran plot for dihedral Phi and Psi angles of aminoacid residues (Laskowski, MacArthur, Moss, &
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Analysis on subunits of heat labile enterotoxin of Escherichia coli
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Thornton, 1993). All modeled subunits were superimposed using pyMOL (DeLano, 2002).
understanding their molecular-level interaction with all chains of LT.
2.5. Selection of ligands
2.6. Molecular docking
Proanthocyanidins (CID 108065) IUPAC Name: (3R)2-(3,5-dihydroxy-4-methoxyphenyl)-8-[(2R,3R,4R)-3,5,7trihydroxy-2-(4-hydroxyphenyl)-3,4-dihydro-2H chromen-4-yl]-3,4-dihydro-2H-chromene-3,5,7-triol. Polymer composition of this compound has been patented in United States (Patent Number: US 7341,744 B1) and this is effective against secretory diarrhea by acting on cystic fibrosis transmembrane receptor. Pentatriacontan-5-one [CID 54409273] is a long chain (C35) ketone present in the bark of Ficus benghalensis Linn. Prediction of these compounds by in silico model (docking) would help in
Molecular docking of different chains of LT was subjected to the two ligands using AutoDock4.2 (Goodsell, Morris, & Olson, 1996). Flexible docking using hydrogen module in Autodock tools was performed. Energy minimization of both ligands was done by MMFF94 force field (Halgren, 1996) and Gasteiger partial charges were added. Affinity maps and spacing were generated using the Autogrid program. Lamarckian genetic algorithm (LGA) and the Solis & Wets local search method (Solis & Wets, 1981) were used for docking simulations with 10 different runs up to
Figure 2. MSA for the LTA subunit of different serotypes. The MSA was performed using known structure of an Enterotoxin of E. coli (PDB ID: 1LTS) as reference.
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250,000 energy evaluations. During this process, .2 Å translational step, and quaternion and torsion steps of five were followed.
ensemble. The systems were neutralized by adding Cl− counterions and concluded by MD simulations. 3. Results
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2.7. Molecular dynamics simulations Lowest energy complexes obtained from Autodock were considered for performing molecular dynamics (MD) simulations. Topology file and other force field parameters were generated using the PRODRG program (Schuttelkopf & Van Aalten, 2004). MD simulations of modeled proteins were performed using GROMACS 4.6 package with the OPLS-AA/L all-atom force field (Berendsen, van der Spoel, & van Drunen, 1995). Energy minimization followed by the temperature equilibration at the NVT isothermal–isochoric ensemble was performed and the periodic boundary conditions for all three dimensions were obtained. Similarly, the pressure of the system is stabilized at NPT isothermal–isobaric
3.1. Mutation and interface residues MSA of LTA predicted five different mutations in the interface residue region for all serotypes (Figure 2). While for LTB, except K102E in D/H interface, there is no mutation in other interface residues (Figure 3). The reason for these conserved regions in LTB may be due to its significance in binding to receptor. The unique mutation for LTA with respect to serotype is high, where as no such difference is observed in LTB. This would further increase the importance of LTB subunit. Mutation in the interface residue position is depicted in graph (Figure 4). The mutated residue position and the number of mutated residues per strain are briefly explained in Tables 2 and 3. All mutated residues were present in
Figure 3. MSA for the LTB subunit of different serotypes. The MSA was performed using known structure of an Enterotoxin of E. coli (PDB ID: 1LTS) as reference.
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Analysis on subunits of heat labile enterotoxin of Escherichia coli
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Figure 4. Representation of mutated residue positions in serotypes to interface residues in LT complex as a function of their residue position identified using ΔASA measure.
Table 2. Strain 121-I 136-I PE0415 PE0615 4321-1 214-III 4702-1 4692-1 2781-5 63-V 61A-4 PE0534
Mutations in LTA sequences among different serotypes as summarized from MSA. Serotype
Length
Number of mutated residues
O48:H21 O88:H25 O152:H2 ONT:H9 ONT:HONT:HNT O167:H5 ONT:HO78:H12 O159:H17 O78:H12 O106:H40
237 237 237 237 237 237 237 237 237 237 237 237
2 2 2 4 4 4 3 4 5 5 4 5
Mutation R1 K, R1 K, R1 K, R1 K, R1 K, R1 K, R1 K, R1 K, R1 K, R1 K, R1 K, R1 K,
R232G R232G T200A R15H, M20I, E210 K R15H, M34I, E210 K Q182R, E210 K, N231S D11Y, E210 K M34I, T190A, I229 M Y3C, S187L, G193D, S221T D157G, S187L, G193D, S221T S187L, G193D, S221T, P9S, S187L, G193D, S221T
Accession number ABV01314.1 ABV01310.1 ABV01320.1 ABV01330.1 ABV01328.1 ABV01324.1 ABV01322.1 ABV01326.1 ABV01336.1 ABV01332.1 ABV01334.2 ABV01318.1
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Table 3.
Mutations in LTB sequences among different serotypes as summarized from MSA.
Strain
Serotype
225-IV 121-I 136-I PE0415 PE0615 4321-1 214-III 4702-1 4692-1 2781-5 63-V 61A-4 PE0534
O148:H28 O48:H21 O88:H25 O152:H2 ONT:H9 ONT:HONT:HNT O167:H5 ONT:HO78:H12 O159:H17 O78:H12 O106:H40
Figure 5.
Length
Number of mutated residues
103 103 103 103 103 103 103 103 103 103 103 103 103
1 3 4 4 3 3 3 3 3 4 4 4 4
Mutation K102E K102E,T4S, E46A R13H, K102E, T4S, E46A R13H, K102E, T4S, E46A K102E, T4S, E46A K102E, T4S, E46A K102E, T4S, E46A K102E, T4S, E46A K102E, T4S, E46A T75A, K102E, T4S, E46A T75A, K102E, T4S, E46A T75A, K102E, T4S, E46A T75A, K102E, T4S, E46A
Accession number ABV01316.1 ABV01314.1 ABV01310.1 ABV01320.1 ABV01330.1 ABV01328.1 ABV01324.1 ABV01322.1 ABV01326.1 ABV01336.1 ABV01332.1 ABV01334.2 ABV01318.1
Structure of E. coli heat-labile enterotoxin, LTA and LTB subunits with the monomers and the total labile toxin.
exposed region including the mutated interface except, the buried LTA-M20I and buried interface E210 K. Number of strains which share the common mutation and either they are synonymous or non-synonymous are also explained. Mutations like LTB-K102E, LTB-T4S,
LTB-E46A, and LTA-R1 K were prevalent in 85% and more of data-set sequences. LTB being a pentameric subunit in the form of ring, interface residues are analyzed for three of the monomers (D, E, and H) (Figures 5 and 6). In LTA among 44
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Analysis on subunits of heat labile enterotoxin of Escherichia coli
Figure 6.
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LTB assembly of D, E, and H monomers and interface between monomers.
mutations, 11 lie on the interface residue between A/B5 complexes. For LTB, the 102 amino acid residue K102E was the only mutation in the D/H interface residue among the total of 43 mutations. The number of mutations in different strains, types, and nature of mutation (synonymous or non-synonymous), the residue position (exposed, buried or interface) is well documented (Table 4). All of the mutated residues were found exposed except the buried interface LTA [E210 K] and buried LTA [M20I]. Mutations were mapped to the three-dimensional structure of the LT using pyMOL (Figure 7). 3.2. Molecular modeling The lists of serotypes are grouped through phylogenetic classification (Figures 8 and 9) for LTA, LTB, and LTC (c domain of subunit A). Based on the grouping among completely identical residues, a representative was chosen for further analysis. The modeled chains are superimposed (Figure 10). A and B subunits are aligned distinctly with minimal dissimilarity, but C chain remains unique for individual serotypes. C chain lies in the interjection between A and B subunit. It also remains the crucial part of dissociation between the A and B subunits. Hence, the uniqueness is conserved in individual serotypes for its specific dissociation and association during the course of action. Only a proper dissociation might facilitate the removal of B subunit thereby allowing for further interaction with the surface receptors. Though A
subunit is catalytically active, from the above analysis, the highest priority in terms of functionality of the toxin is for C followed by B then A subunits. 3.3. Docking The energy-minimized toxin models are docked with the ligands proanthocyanidin and pentatriacontan-5-one (Figure 11). Hydrophobic and hydrogen bonding interactions between the ligand and the residues were illustrated in the two-dimensional plot (Figure 12). Proanthocyanidin possess more number of hydrogen bonding interaction with all chains of the toxin (Table 5). Although pentatriacontan-5-one has hydrophobic interaction with all chains, it is less suitable as there is only one couple of hydrogen bonding interaction. One with A and one with B chain among all the serotypes were analyzed. 3.4. Molecular dynamics The docked complexes with lowest energy interaction (Table 6) in proanthocyanidin with the three chains were subjected to final molecular dynamics simulation (Figure 13). This would facilitate understanding of the stability, conformational change, and dynamics with respect to different time scales. RMSD of ligands to A and B chain remain leveled off after initial rise (Figure 14). The fluctuation in C domain may be because it is not an independent subunit and also it has shorter
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Table 4. Mutations, their sequence positions, change in amino acid types, relative occurrence at surface, interface, and interior regions of the complex in different serotypes are given. LTA Mutation P9S D157G S221T G193D
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S187L Y3C I229 M T190A D11Y N231S Q182R M34I R15H M20I E210 K T200A R1 K R232G LTB T75A R13H E46A T4S K102E
Nature of mutations
Number of strains
Non polar to Polar (0) Polar(-) to Non polar Polar(0) to Polar(0) Non polar to Polar (-) Polar(0) to Non polar Polar(0) to Non polar Non polar to Non polar Polar(0) to Non polar Polar(-) to Polar(0) Polar(0) to Polar(0) Polar(0) to Polar(+) Non polar to Non polar Polar(+) to Polar(0) Non polar to Non polar Polar(-) to Polar(+) Polar(0) to Non polar Polar(+) to Polar(+) Polar(+) to Non polar Polar(0) to Non polar Polar(+) to Polar(0) Polar(-) to Non Polar Polar(0) to Polar(0) Polar(+) to Polar(-)
1
U
PE0534
1
U
63-V
U
PE0534, 61A-4, 63-V, 2781-5
4
U
PE0534, 63-V, 61A-4, 2781-5
4
U
PE0534, 63-V, 61A-4, 2781-6
1
U
2781-5
U
4692-1
1
U
4692-1
1
U
4702-1
1
U
214-III
1
U
214-III
2
U
4321-1, 4692-1
2
U
PE0615, 4321-1
4
1
LTA/LTB interface
U
U
1 4
Buried Exposed Strain (s)
U
U
PE0615
U
PE0615, 4321-1, 214-III, 4702-1
1
U
PE0415
12
U U
PE0534, 61A-4, 63-V, 2781-5, 4692-1, 4702-1, 214-III, 4321-1, PE0615, PE0415, 136-I, 121-I 121-I, 136-I
4
U
PE0534, 61A-4, 63-V, 2781-5
2
U
PE0415, 136-I
12
U
12
U
PE0534, 61A-4, 63-V, 2781-5, 4692-1, 4702-1, 214-III, 4321-1, PE0615, PE0415, 136-I, 121-I PE0534, 61A-4, 63-V, 2781-5, 4692-1, 4702-1, 214-III, 4321-1, PE0615, PE0415, 136-I, 121-I PE0534, 61A-4, 63-V, 2781-5, 4692-1, 4702-1, 214-III, 4321-1, PE0615, PE0415, 136-I, 121-I, 225-IV
2
13
U
U
amino acid content. These dynamic changes in RMSD are reflected as variation in receptor image (Figure 13). 4. Discussion The study is unique as the protein is analyzed by individual chains and not as a whole. LT is a toxin which is functionally active only when its chains are dissociated.
U
Prevalence of mutation among different residues and their position either at interface residues or at the surface or buried helps in understanding the toxin. Even though many mutation studies have been conducted in ETEC toxins previously with few other parameters, we found it relevant in defining the mutation in terms of subunit interactions and interface residues by finding the change in accessible surface area. The study reveals the presence
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Analysis on subunits of heat labile enterotoxin of Escherichia coli
Figure 7.
Mutated residues highlighted in the structure of E. coli heat-labile enterotoxin, LTA and LTB monomer.
Figure 8.
Phylogenetic tree for A subsequence (top) and C subsequence (below) of LTA chain.
of significant mutations in the toxins which directed us to locate the mutated positions and its structural significance toward understanding its functional role. The results also depict that majority of mutations in LTA and LTB are at solvent-exposed regions compared to inter-
9
face regions. It is clear that interface residues are significant in holding the interaction between subunits. So, random mutations are unlikely. The complex formation involves intersubunit interactions at the interfaces. This figures out that mutations are at structurally relevant
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Phylogenetic tree for LTB subunit.
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Figure 9.
Figure 10. Heat-labile enterotoxin modelled structure for different serotypes aligned together. (a) Subunit A, (b) Monomer of subunit B, (c) Domain C of subunit A.
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Analysis on subunits of heat labile enterotoxin of Escherichia coli
Figure 11.
Skeleton structure of the selected ligands as shown in pubchem.
Figure 12.
Hydrophobic and hydrogen bonding interactions between the ligands LTB.
positions which could be significant in considering pathogenesis and may serve better toward protein-based vaccine design. The mutation study can help in designing novel mutant varieties of toxins for therapeutics like subunit vaccines. Our analysis predicts that C domain has a significant impact on pathogenesis followed by B and A subunits. Interaction of proanthocyanidin with the
11
chains helps in understanding the molecular-level action of this compound against secretory diarrhea. Instead of LT as a whole toxin, this interactions study helped to understand the ligands preference for all the three subunits of LT receptor thus paving a novel way to target individual chains or subunits rather than the complete LT.
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Table 5.
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Serotype name
List of hydrophobic interacting residues and residues interacting through hydrogen bonding (highlighted in bold). Pentatriacontan-5-one
Proanthocyanidin
A
B
C
A
B
C
2781-5
ARG30, GLN33, MET34, ILE36, ASN37, TYR39, ASP40, ARG43, GLY163, PHE164, PRO165
TYR25, LYS28, VAL29, GLN32, ILE33, ASP36, TYR37
TRP171, ARG172, ILE177, HIS178, HIS179, ALA180, PEO181, GLN182, CYS184, GLY185,
LEU8, VAL50, ALA64, ILE65, ARG67, MET68, ILE96, ALA97, LA98, [ILE99]
SER27, THR35, TYR37, [ARG31, PHE34, GLN38]
PE0615
LYS2, ASN3, THR5, ARG166, TYR167, ASN170
LEU8, TYR12, GLN61, TRP88, ALA97, ALA98, ILE99, MET101 GLN16, TYR18, ARG35, THR47, PRO93
TYR3, LEU61, SER62, SER65, TYR106, GLU107, GLN108, TYR125,
[ASP21, THR108, TYR163, ASP165, ASN170, LEU171], LYS22, ALA107, TYR143, TYR168, ARG169 ARG8, GLU12, SER16, MET20, HIS24, ASN25, PHE49, TYR52. [GLY18, ARG22, GLY23]
[GLN49, VAL52, SER55], GLU51, GLN56, LYS91, THR92
121-I
TYR22, LYS25, TYR26, LYS29, VAL30, GLN33, TYR38, ILE34 ARG24, GLN27, SER28, LYS31, ILE34, PHE35,
[TYR26], VAL30, LYS31, GLN33, ILE34, PHE35, ILE48, ARG49, LEU52, [ASN46, ASP50]
225-IV
ASN95, ASP96, GLY99, PRO105, GLN108,
TYR22, LEU23, TYR26, GLN27, VAL30, ILE34, PHE35, TYR38
ILE36, ASN37, LEU113, ARG160, LEU161, GLY163, PHE164, TRP171, PRO181, [LEU38, TYR56, CYS184]
THR4, LEU8, ILE99,SER100, MET101, [GLN3, ILE5]
ASN1, ARG4, THR5, ILE6, LEU18, [SER2]
GLU11, TYR12, GLN56, HIS57, GLN61, TRP88, [ARG13, ASN14]
SER2, ARG4, THR5, ILE6, GLU14, [ASN1]
[GLU51, HIS57, GLN61], ALA64, ILE65, MET68, TRP88, ILE96, ALA97
[SER28, GLN39], LYS31, ARG32, PHE35, SER36, TYR38
1372-1
PE0415
LYS1, LEU61, ASP96, GLY99, VAL100, ASN151, ILE152, PRO154, ALA155, GLU156, TRP176, TYR159,
214-III
ARG22, THR45, GLN46, PHE49, THR47, ILE73, TYR52, [SER72]
4692-1
TYR39, LEU61, ASN93, ASN95, ASP96, GLY99, VAL100, TYR101, SER102, PRO105, VAL110, ILE152, HIS168
CYS9, SER10, TYR12, THR15, ILE17, THR19, ILE20, ASN21, THR6, GLU7, THR15, GLN16, ASN89, ASN90, THR92, [SER10] ASN14, TYR18, SER44, GLY45, GLU46, ASN89, ASN90, ASN94, SER26, TYR27, THR28, GLU29, THR41, GLY45, ARG73, LEU77
LEU18, SER19, TYR22, LEU23, TYR26, GLN27, VAL30, LYS31, PHE35, ILE21, ARG24, GLU25, SER28, PHE35, TYR38, GLN39, SER40
TYR26, GLN27, VAL30, LYS31, ILE34, PHE35, TYR38, GLN39, SER40, SER19, TYR22, LEU23, TYR26, GLN27, VAL30, ILE34, PHE35, TYR38
[LEU161], ILE36, ASN37, LEU38, TYR56, LEU113, ARG160, ALA162, GLY163, PHE164, TRP171, PRO181, CYS184
TYR27, THR28, SER30, MET31, [GLU29, ARG73]
ILE36, ASN37, TYR56, GLY163, PHE164, TRP171, PRO181, [LEU38, ARG160, LEU161, CYS184]
PHE35, TYR38, GLN39
HIS24, TYR27, PHE28, ARG30, GLN33, ILE36, GLY114, [THR32, ILE34]
LEU52, [TYR45, ILE48, ARG49, ASP50]
(Continued)
Analysis on subunits of heat labile enterotoxin of Escherichia coli Table 5.
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Serotype name
(Continued). Pentatriacontan-5-one A
B
4702-1
TYR39, TYR101, SER102, PRO103, PRO105, TYR106, [ARG43]
61A-4
ASN95, ASP96, GLY99, PRO105, TYR106, GLN108, PRO154, ALA155, GLU156, TYR159, THR87, ASP96, GLY99, VAL100, ASN151, ILE152, ALA155, TYR159, GLU173, GLU174, TRP176, ILE36, PRO89, LEU113, ASN151, ILE152, ALA153, PRO154, ASP157, LEU161
4321-1
PE0534
Table 6.
Proanthocyanidin C
A
B
THR10, CYS11, GLU14, THR15, LEU18, SER19, ILE21, TYR22, LYS25
PRO89, ASN149, LEU150, ILE152, ALA153, PRO154, [ASN151]
SER28, LYS31, ARG32, SER36, GLN39, [PHE35]
LYS14, GLY17, TYR27, PHE28, PRO117, TYR118, SER119, GLU141, [ARG30, THR32, MET34], HIS24, TYR27, PHE28, ASP29, GLN33
Energy values (kcal/mol) of three chains in different serotypes with the ligands.
Serotype name
Figure 13.
C
[ASP40], ASN37, TYR39, ARG43, GLY163, PHE164, PRO165,
Pentatriacontan-5-one
2781-5 PE0615 121-I 225-IV 1372-1 PE0415 214-III 4692-1 4702-1 61A-4 4321-1 PE0534
13
Proanthocyanidin
A
B
C
A
B
C
−.89 −1.54 −1.67 −2
−.34 −1.34 −1.7 −.36 −1.39 −.83
−.45 −2.29 .45 −2.97 −3.06 −.38 −0.83 −1.6 −3.02
−9.88 −15.09 −10.51 −10.46
−9.27 −9.14 −9.66 −9.34 −10.87 −10.73
−8.95 −8.06 −9.44 −7.7 −7.29 −8.31 −7.45 −8.25 −8.11
−1.74 −.29 −2.09 −2.2 −.44 −1.05 −2.79
−10.23 −11.17 −10.61 −8.24 −10.65 −9.5 −10.01
Molecular dynamics of chains A, B, and C (a, b, c) showing change in conformation at different time intervals.
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Figure 14.
RMSD profile of different chains.
Acknowledgments The authors would like to acknowledge VIT University, Vellore for their constant support and facilities provided for doing excellence in research.
References Abola, E. E., Bernstein, F. C., & Koetzle, T. F. (1984). The protein data bank. Neutrons in Biology, 27, 441. Allen, K. P., Randolph, M. M., & Fleckenstein, J. M. (2006). Importance of heat-labile enterotoxin in colonization of the adult mouse small intestine by human enterotoxigenic Escherichia coli strains. Infection and Immunity, 74, 869–875. Berberov, E. M., Zhou, Y., Francis, D. H., Scott, M. A., Kachman, S. D., & Moxley, R. A. (2004). Relative importance of heat-labile enterotoxin in the causation of severe diarrheal disease in the gnotobiotic piglet model by a strain of enterotoxigenic Escherichia coli that produces multiple enterotoxins. Infection and Immunity, 72, 3914–3924. Berendsen, H. J. C., van der Spoel, D., & van Drunen, R. (1995). GROMACS: A message-passing parallel molecular dynamics implementation. Computer Physics Communications, 91, 43–56. DeLano, W. L. (2002). The PyMOL molecular graphics system. Fiser, A., & Šali, A. (2003). Modeller: Generation and refinement of homology-based protein structure models. Methods in Enzymology, 374, 461–491.
Goodsell, D. S., Morris, G. M., & Olson, A. J. (1996). Automated docking of flexible ligands: Applications of autodock. Journal of Molecular Recognition, 9, 1–5. Halgren, T. A. (1996). Merck molecular force field. I. Basis, form, scope, parameterization, and performance of MMFF94. Journal of Computational Chemistry, 17, 490–519. Laskowski, R. A., MacArthur, M. W., Moss, D. S., & Thornton, J. M. (1993). PROCHECK: A program to check the stereochemical quality of protein structures. Journal of Applied Crystallography, 26, 283–291. Levine, M. M. (1987). Escherichia coli that cause Diarrhea: enterotoxigenic, enteropathogenic, enteroinvasive, enterohemorrhagic, and enteroadherent. Journal of Infectious Diseases, 155, 377–389. Merritt, E. A., & Hol, W. G. (1995). AB5 toxins. Current Opinion in Structural Biology, 5, 165–171. Nataro, J. P., & Kaper, J. B. (1998). Diarrheagenic Escherichia coli. Clinical Microbiology Reviews, 11, 142–201. Okamoto, K., Nomura, T., Fujii, Y., & Yamanaka, H. (1998). Contribution of the disulfide bond of the A subunit to the action of Escherichia coli heat-labile enterotoxin. Journal of Bacteriology, 180, 1368–1374. Rodrigues, J. F., Mathias-Santos, C., Sbrogio-Almeida, M. E., Amorim, J. H., Cabrera-Crespo, J., Balan, A., & Ferreira, L. C. (2011). Functional diversity of heat-labile toxins (LT) produced by Enterotoxigenic Escherichia coli: Differential enzymatic and immunological activities of LT1 (hLT) and LT4 (pLT). Journal of Biological Chemistry, 286, 5222– 5233. Schüttelkopf, A. W., & van Aalten, D. M. (2004). PRODRG: A tool for high-throughput crystallography of protein– ligand complexes. Acta Crystallographica, Section D: Biological Crystallography, 60, 1355–1363. Solis, F. J., & Wets, R. J.-B. (1981). Minimization by random search techniques. Mathematics of operations research, 6, 19–30. Svennerholm, A. M., & Tobias, J. (2008). Vaccines against enterotoxigenic Escherichia coli. Expert Review of Vaccines, 7, 795–804. Wang, Q., Wang, S., Beutin, L., Cao, B., Feng, L., & Wang, L. (2010). Development of a DNA microarray for detection and serotyping of enterotoxigenic Escherichia coli. Journal of Clinical Microbiology, 48, 2066–2074.
Journal of Biomolecular Structure and Dynamics Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/tbsd20
Analysis and modeling of heat-labile enterotoxins of Escherichia coli suggests a novel space with insights into receptor preference a
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M. Krishna Raja , Asit Ranjan Ghosh , S. Vino & S. Sajitha Lulu
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School of Bio Sciences and Technology, VIT University, Vellore, India Published online: 06 Nov 2014.
Click for updates To cite this article: M. Krishna Raja, Asit Ranjan Ghosh, S. Vino & S. Sajitha Lulu (2014): Analysis and modeling of heatlabile enterotoxins of Escherichia coli suggests a novel space with insights into receptor preference, Journal of Biomolecular Structure and Dynamics, DOI: 10.1080/07391102.2014.974073 To link to this article: http://dx.doi.org/10.1080/07391102.2014.974073
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Journal of Biomolecular Structure and Dynamics, 2014 http://dx.doi.org/10.1080/07391102.2014.974073
Analysis and modeling of heat-labile enterotoxins of Escherichia coli suggests a novel space with insights into receptor preference M. Krishna Raja, Asit Ranjan Ghosh, S. Vino and S. Sajitha Lulu* School of Bio Sciences and Technology, VIT University, Vellore, India Communicated by Ramaswamy H. Sarma
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(Received 20 January 2014; accepted 4 October 2014) Features of heat-labile enterotoxins of Escherichia coli which make them fit to use as novel receptors for antidiarrheals are not completely explored. Data-set of 14 different serovars of enterotoxigenic Escherichia coli producing heat-labile toxins were taken from NCBI Genbank database and used in the study. Sequence analysis showed mutations in different subunits and also at their interface residues. As these toxins lack crystallography structures, homology modeling using Modeller 9.11 led to the structural approximation for the E. coli producing heat-labile toxins. Interaction of modeled toxin subunits with proanthocyanidin, an antidiarrheal showed several strong hydrogen bonding interactions at the cost of minimized energy. The hits were subsequently characterized by molecular dynamics simulation studies to monitor their binding stabilities. This study looks into novel space where the ligand can choose the receptor preference not as a whole but as an individual subunit. Mutation at interface residues and interaction among subunits along with the binding of ligand to individual subunits would help to design a non-toxic labile toxin and also to improve the therapeutics. Keywords: receptor; labile toxin; interface residue; mutation
1. Introduction Enterotoxigenic Escherichia coli (ETEC) play a critical role in causing diarrheal-related illness among mammals (Levine, 1987). It causes travelers’ diarrhea mainly in the developing world (Wang et al., 2010) and also causes diarrhea in infants, children, and adults leading to global health problem. It emphasizes the need to understand and analyze the role of ETEC toxin genes in humans which has a heterohexamer (AB5) complex consisting of catalytically active monomeric A subunit (LTA) and pentameric B subunits (LTB) (Merritt & Hol, 1995). Heat-labile (LT) enterotoxin is one of the essential components in disease pathogenesis resulting in gut lumen dehydration (Nataro & Kaper, 1998). In addition to pathogenicity expression of LT, colonization is an added advantage (Allen, Randolph, & Fleckenstein, 2006; Berberov et al., 2004). Vaccine development is facing hurdles due to the variability of antigens among strains (Svennerholm & Tobias, 2008). It is well documented that the mutation has an impact on toxicity, adjuvant activity, cytotonic effect, cAMP levels, and ADP ribosylation (Rodrigues et al., 2011). Significance of mutation can be deciphered from reports like mutation in cysteine residues which results in degradation of LTA by proteases and thereby reduction in cAMP production (Okamoto, Nomura, Fujii, & Yamanaka, 1998). *Corresponding author. Email: [email protected] © 2014 Taylor & Francis
Therefore, the present study enumerates the necessity of analyzing the subunit sequence for mutation, interface residues, and interaction of ligands with individual subunits which would be useful for developing drugs for treatment and prevention. 2. Methods 2.1. LT data-set Complete sequences of heat-labile enterotoxin (LT) of E. coli were taken from the Genbank database. Among the several hits found, the complete sequences were selected from both the A and B subunit toxin. As illustrated in Figure 1, using keyword search in Genbank database, the respective hits 14 for LTA and 71 for LTB were obtained as search results (Table 1). For LTA, the 14 hits representing E. coli were selected, while for LTB the first 14 hits for full length sequence were selected for the data-set. 2.2. Multiple sequence alignment of LTA and LTB Multiple sequence alignment (MSA) was performed using clustalW2 protein with the substitution matrix PAM, extension penalty of .20, and gap-opening penalty of 10. 1LTS available in the Brookhaven protein data bank (PDB) database (Abola, Bernstein, & Koetzle,
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Figure 1.
Creation of sequence data-set for E. coli labile toxins, LTA and LTB.
Table 1. Data-set summary for LTA and LTB sequences from various serotypes. Number of sequences Strain 2781–5 61A-4 63-V PE0615 4321–1 4692–1 214-III 4702–1 PE0415 PE0534 225-IV 121-I 1372–1 136-I Total
Serotype
LTA
LTB
O78:H12 O78:H12 O159:H17 ONT:H9 ONT:HONT:HONT:HNT O167:H5 O152:H2 O106:H40 O148:H28 O48:H21 O23:H28 O88:H25
1 1 1 1 1 1 1 1 1 1 1 1 1 1 14
1 1 1 1 1 1 1 1 1 1 1 1 1 1 14
1984) is used as the reference sequence in this study. The alignment was done to predict mutation in the toxin. The mutations were further analyzed to locate their presence in the interface residue positions, as they are vital in forming the structural assembly and in deciding the functional role. For mutations corresponding to the gaps of the reference sequence, the amino acid which appears most is taken as reference. 2.3. Interface residues Interface residues were determined by calculating the change in solvent-accessible surface area by prosurf
[http://curie.utmb.edu] and in the interacting residues by protInDB [http://protindb.cs.iastate.edu/]. The interface residues and their mutations are given in MSA. Among the interface residues identified in the different subunits of the toxin, the interface residues between the A and the B5 subunit and one representative of the D monomer from the entire B subunit were taken into account. In the B subunit, the interface residues occur between the two adjacent monomers. D monomer has its adjacent interface interactions with E and H monomers. As they are five monomers, analyzing one of the monomers properties implies the rest. 2.4. Molecular modeling There is no X-ray crystallographic structure for the set of sequences in the data-set. Template for modeling was chosen by the maximum identity and statistical E measure of the query sequence with the PDB database (Abola et al., 1984) by using blast algorithm. Threedimensional homology models were constructed for target proteins using LT crystal structures with PDB ID: 1LTA and 1LTB for A and B chains, respectively. Sequences of subunit A, C (part of subunit A) and B were modeled using MODELLER version 9.11 (Fiser & Šali, 2003). Out of five modeled proteins for each sequence, the best one was selected based on the DOPE score. Homology modeled proteins were energy minimized after adding hydrogen atoms and conformation of the models was evaluated using procheck by visualizing the Ramachandran plot for dihedral Phi and Psi angles of aminoacid residues (Laskowski, MacArthur, Moss, &
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Thornton, 1993). All modeled subunits were superimposed using pyMOL (DeLano, 2002).
understanding their molecular-level interaction with all chains of LT.
2.5. Selection of ligands
2.6. Molecular docking
Proanthocyanidins (CID 108065) IUPAC Name: (3R)2-(3,5-dihydroxy-4-methoxyphenyl)-8-[(2R,3R,4R)-3,5,7trihydroxy-2-(4-hydroxyphenyl)-3,4-dihydro-2H chromen-4-yl]-3,4-dihydro-2H-chromene-3,5,7-triol. Polymer composition of this compound has been patented in United States (Patent Number: US 7341,744 B1) and this is effective against secretory diarrhea by acting on cystic fibrosis transmembrane receptor. Pentatriacontan-5-one [CID 54409273] is a long chain (C35) ketone present in the bark of Ficus benghalensis Linn. Prediction of these compounds by in silico model (docking) would help in
Molecular docking of different chains of LT was subjected to the two ligands using AutoDock4.2 (Goodsell, Morris, & Olson, 1996). Flexible docking using hydrogen module in Autodock tools was performed. Energy minimization of both ligands was done by MMFF94 force field (Halgren, 1996) and Gasteiger partial charges were added. Affinity maps and spacing were generated using the Autogrid program. Lamarckian genetic algorithm (LGA) and the Solis & Wets local search method (Solis & Wets, 1981) were used for docking simulations with 10 different runs up to
Figure 2. MSA for the LTA subunit of different serotypes. The MSA was performed using known structure of an Enterotoxin of E. coli (PDB ID: 1LTS) as reference.
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250,000 energy evaluations. During this process, .2 Å translational step, and quaternion and torsion steps of five were followed.
ensemble. The systems were neutralized by adding Cl− counterions and concluded by MD simulations. 3. Results
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2.7. Molecular dynamics simulations Lowest energy complexes obtained from Autodock were considered for performing molecular dynamics (MD) simulations. Topology file and other force field parameters were generated using the PRODRG program (Schuttelkopf & Van Aalten, 2004). MD simulations of modeled proteins were performed using GROMACS 4.6 package with the OPLS-AA/L all-atom force field (Berendsen, van der Spoel, & van Drunen, 1995). Energy minimization followed by the temperature equilibration at the NVT isothermal–isochoric ensemble was performed and the periodic boundary conditions for all three dimensions were obtained. Similarly, the pressure of the system is stabilized at NPT isothermal–isobaric
3.1. Mutation and interface residues MSA of LTA predicted five different mutations in the interface residue region for all serotypes (Figure 2). While for LTB, except K102E in D/H interface, there is no mutation in other interface residues (Figure 3). The reason for these conserved regions in LTB may be due to its significance in binding to receptor. The unique mutation for LTA with respect to serotype is high, where as no such difference is observed in LTB. This would further increase the importance of LTB subunit. Mutation in the interface residue position is depicted in graph (Figure 4). The mutated residue position and the number of mutated residues per strain are briefly explained in Tables 2 and 3. All mutated residues were present in
Figure 3. MSA for the LTB subunit of different serotypes. The MSA was performed using known structure of an Enterotoxin of E. coli (PDB ID: 1LTS) as reference.
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Figure 4. Representation of mutated residue positions in serotypes to interface residues in LT complex as a function of their residue position identified using ΔASA measure.
Table 2. Strain 121-I 136-I PE0415 PE0615 4321-1 214-III 4702-1 4692-1 2781-5 63-V 61A-4 PE0534
Mutations in LTA sequences among different serotypes as summarized from MSA. Serotype
Length
Number of mutated residues
O48:H21 O88:H25 O152:H2 ONT:H9 ONT:HONT:HNT O167:H5 ONT:HO78:H12 O159:H17 O78:H12 O106:H40
237 237 237 237 237 237 237 237 237 237 237 237
2 2 2 4 4 4 3 4 5 5 4 5
Mutation R1 K, R1 K, R1 K, R1 K, R1 K, R1 K, R1 K, R1 K, R1 K, R1 K, R1 K, R1 K,
R232G R232G T200A R15H, M20I, E210 K R15H, M34I, E210 K Q182R, E210 K, N231S D11Y, E210 K M34I, T190A, I229 M Y3C, S187L, G193D, S221T D157G, S187L, G193D, S221T S187L, G193D, S221T, P9S, S187L, G193D, S221T
Accession number ABV01314.1 ABV01310.1 ABV01320.1 ABV01330.1 ABV01328.1 ABV01324.1 ABV01322.1 ABV01326.1 ABV01336.1 ABV01332.1 ABV01334.2 ABV01318.1
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Table 3.
Mutations in LTB sequences among different serotypes as summarized from MSA.
Strain
Serotype
225-IV 121-I 136-I PE0415 PE0615 4321-1 214-III 4702-1 4692-1 2781-5 63-V 61A-4 PE0534
O148:H28 O48:H21 O88:H25 O152:H2 ONT:H9 ONT:HONT:HNT O167:H5 ONT:HO78:H12 O159:H17 O78:H12 O106:H40
Figure 5.
Length
Number of mutated residues
103 103 103 103 103 103 103 103 103 103 103 103 103
1 3 4 4 3 3 3 3 3 4 4 4 4
Mutation K102E K102E,T4S, E46A R13H, K102E, T4S, E46A R13H, K102E, T4S, E46A K102E, T4S, E46A K102E, T4S, E46A K102E, T4S, E46A K102E, T4S, E46A K102E, T4S, E46A T75A, K102E, T4S, E46A T75A, K102E, T4S, E46A T75A, K102E, T4S, E46A T75A, K102E, T4S, E46A
Accession number ABV01316.1 ABV01314.1 ABV01310.1 ABV01320.1 ABV01330.1 ABV01328.1 ABV01324.1 ABV01322.1 ABV01326.1 ABV01336.1 ABV01332.1 ABV01334.2 ABV01318.1
Structure of E. coli heat-labile enterotoxin, LTA and LTB subunits with the monomers and the total labile toxin.
exposed region including the mutated interface except, the buried LTA-M20I and buried interface E210 K. Number of strains which share the common mutation and either they are synonymous or non-synonymous are also explained. Mutations like LTB-K102E, LTB-T4S,
LTB-E46A, and LTA-R1 K were prevalent in 85% and more of data-set sequences. LTB being a pentameric subunit in the form of ring, interface residues are analyzed for three of the monomers (D, E, and H) (Figures 5 and 6). In LTA among 44
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Analysis on subunits of heat labile enterotoxin of Escherichia coli
Figure 6.
7
LTB assembly of D, E, and H monomers and interface between monomers.
mutations, 11 lie on the interface residue between A/B5 complexes. For LTB, the 102 amino acid residue K102E was the only mutation in the D/H interface residue among the total of 43 mutations. The number of mutations in different strains, types, and nature of mutation (synonymous or non-synonymous), the residue position (exposed, buried or interface) is well documented (Table 4). All of the mutated residues were found exposed except the buried interface LTA [E210 K] and buried LTA [M20I]. Mutations were mapped to the three-dimensional structure of the LT using pyMOL (Figure 7). 3.2. Molecular modeling The lists of serotypes are grouped through phylogenetic classification (Figures 8 and 9) for LTA, LTB, and LTC (c domain of subunit A). Based on the grouping among completely identical residues, a representative was chosen for further analysis. The modeled chains are superimposed (Figure 10). A and B subunits are aligned distinctly with minimal dissimilarity, but C chain remains unique for individual serotypes. C chain lies in the interjection between A and B subunit. It also remains the crucial part of dissociation between the A and B subunits. Hence, the uniqueness is conserved in individual serotypes for its specific dissociation and association during the course of action. Only a proper dissociation might facilitate the removal of B subunit thereby allowing for further interaction with the surface receptors. Though A
subunit is catalytically active, from the above analysis, the highest priority in terms of functionality of the toxin is for C followed by B then A subunits. 3.3. Docking The energy-minimized toxin models are docked with the ligands proanthocyanidin and pentatriacontan-5-one (Figure 11). Hydrophobic and hydrogen bonding interactions between the ligand and the residues were illustrated in the two-dimensional plot (Figure 12). Proanthocyanidin possess more number of hydrogen bonding interaction with all chains of the toxin (Table 5). Although pentatriacontan-5-one has hydrophobic interaction with all chains, it is less suitable as there is only one couple of hydrogen bonding interaction. One with A and one with B chain among all the serotypes were analyzed. 3.4. Molecular dynamics The docked complexes with lowest energy interaction (Table 6) in proanthocyanidin with the three chains were subjected to final molecular dynamics simulation (Figure 13). This would facilitate understanding of the stability, conformational change, and dynamics with respect to different time scales. RMSD of ligands to A and B chain remain leveled off after initial rise (Figure 14). The fluctuation in C domain may be because it is not an independent subunit and also it has shorter
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Table 4. Mutations, their sequence positions, change in amino acid types, relative occurrence at surface, interface, and interior regions of the complex in different serotypes are given. LTA Mutation P9S D157G S221T G193D
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S187L Y3C I229 M T190A D11Y N231S Q182R M34I R15H M20I E210 K T200A R1 K R232G LTB T75A R13H E46A T4S K102E
Nature of mutations
Number of strains
Non polar to Polar (0) Polar(-) to Non polar Polar(0) to Polar(0) Non polar to Polar (-) Polar(0) to Non polar Polar(0) to Non polar Non polar to Non polar Polar(0) to Non polar Polar(-) to Polar(0) Polar(0) to Polar(0) Polar(0) to Polar(+) Non polar to Non polar Polar(+) to Polar(0) Non polar to Non polar Polar(-) to Polar(+) Polar(0) to Non polar Polar(+) to Polar(+) Polar(+) to Non polar Polar(0) to Non polar Polar(+) to Polar(0) Polar(-) to Non Polar Polar(0) to Polar(0) Polar(+) to Polar(-)
1
U
PE0534
1
U
63-V
U
PE0534, 61A-4, 63-V, 2781-5
4
U
PE0534, 63-V, 61A-4, 2781-5
4
U
PE0534, 63-V, 61A-4, 2781-6
1
U
2781-5
U
4692-1
1
U
4692-1
1
U
4702-1
1
U
214-III
1
U
214-III
2
U
4321-1, 4692-1
2
U
PE0615, 4321-1
4
1
LTA/LTB interface
U
U
1 4
Buried Exposed Strain (s)
U
U
PE0615
U
PE0615, 4321-1, 214-III, 4702-1
1
U
PE0415
12
U U
PE0534, 61A-4, 63-V, 2781-5, 4692-1, 4702-1, 214-III, 4321-1, PE0615, PE0415, 136-I, 121-I 121-I, 136-I
4
U
PE0534, 61A-4, 63-V, 2781-5
2
U
PE0415, 136-I
12
U
12
U
PE0534, 61A-4, 63-V, 2781-5, 4692-1, 4702-1, 214-III, 4321-1, PE0615, PE0415, 136-I, 121-I PE0534, 61A-4, 63-V, 2781-5, 4692-1, 4702-1, 214-III, 4321-1, PE0615, PE0415, 136-I, 121-I PE0534, 61A-4, 63-V, 2781-5, 4692-1, 4702-1, 214-III, 4321-1, PE0615, PE0415, 136-I, 121-I, 225-IV
2
13
U
U
amino acid content. These dynamic changes in RMSD are reflected as variation in receptor image (Figure 13). 4. Discussion The study is unique as the protein is analyzed by individual chains and not as a whole. LT is a toxin which is functionally active only when its chains are dissociated.
U
Prevalence of mutation among different residues and their position either at interface residues or at the surface or buried helps in understanding the toxin. Even though many mutation studies have been conducted in ETEC toxins previously with few other parameters, we found it relevant in defining the mutation in terms of subunit interactions and interface residues by finding the change in accessible surface area. The study reveals the presence
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Analysis on subunits of heat labile enterotoxin of Escherichia coli
Figure 7.
Mutated residues highlighted in the structure of E. coli heat-labile enterotoxin, LTA and LTB monomer.
Figure 8.
Phylogenetic tree for A subsequence (top) and C subsequence (below) of LTA chain.
of significant mutations in the toxins which directed us to locate the mutated positions and its structural significance toward understanding its functional role. The results also depict that majority of mutations in LTA and LTB are at solvent-exposed regions compared to inter-
9
face regions. It is clear that interface residues are significant in holding the interaction between subunits. So, random mutations are unlikely. The complex formation involves intersubunit interactions at the interfaces. This figures out that mutations are at structurally relevant
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Phylogenetic tree for LTB subunit.
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Figure 9.
Figure 10. Heat-labile enterotoxin modelled structure for different serotypes aligned together. (a) Subunit A, (b) Monomer of subunit B, (c) Domain C of subunit A.
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Analysis on subunits of heat labile enterotoxin of Escherichia coli
Figure 11.
Skeleton structure of the selected ligands as shown in pubchem.
Figure 12.
Hydrophobic and hydrogen bonding interactions between the ligands LTB.
positions which could be significant in considering pathogenesis and may serve better toward protein-based vaccine design. The mutation study can help in designing novel mutant varieties of toxins for therapeutics like subunit vaccines. Our analysis predicts that C domain has a significant impact on pathogenesis followed by B and A subunits. Interaction of proanthocyanidin with the
11
chains helps in understanding the molecular-level action of this compound against secretory diarrhea. Instead of LT as a whole toxin, this interactions study helped to understand the ligands preference for all the three subunits of LT receptor thus paving a novel way to target individual chains or subunits rather than the complete LT.
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Table 5.
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Serotype name
List of hydrophobic interacting residues and residues interacting through hydrogen bonding (highlighted in bold). Pentatriacontan-5-one
Proanthocyanidin
A
B
C
A
B
C
2781-5
ARG30, GLN33, MET34, ILE36, ASN37, TYR39, ASP40, ARG43, GLY163, PHE164, PRO165
TYR25, LYS28, VAL29, GLN32, ILE33, ASP36, TYR37
TRP171, ARG172, ILE177, HIS178, HIS179, ALA180, PEO181, GLN182, CYS184, GLY185,
LEU8, VAL50, ALA64, ILE65, ARG67, MET68, ILE96, ALA97, LA98, [ILE99]
SER27, THR35, TYR37, [ARG31, PHE34, GLN38]
PE0615
LYS2, ASN3, THR5, ARG166, TYR167, ASN170
LEU8, TYR12, GLN61, TRP88, ALA97, ALA98, ILE99, MET101 GLN16, TYR18, ARG35, THR47, PRO93
TYR3, LEU61, SER62, SER65, TYR106, GLU107, GLN108, TYR125,
[ASP21, THR108, TYR163, ASP165, ASN170, LEU171], LYS22, ALA107, TYR143, TYR168, ARG169 ARG8, GLU12, SER16, MET20, HIS24, ASN25, PHE49, TYR52. [GLY18, ARG22, GLY23]
[GLN49, VAL52, SER55], GLU51, GLN56, LYS91, THR92
121-I
TYR22, LYS25, TYR26, LYS29, VAL30, GLN33, TYR38, ILE34 ARG24, GLN27, SER28, LYS31, ILE34, PHE35,
[TYR26], VAL30, LYS31, GLN33, ILE34, PHE35, ILE48, ARG49, LEU52, [ASN46, ASP50]
225-IV
ASN95, ASP96, GLY99, PRO105, GLN108,
TYR22, LEU23, TYR26, GLN27, VAL30, ILE34, PHE35, TYR38
ILE36, ASN37, LEU113, ARG160, LEU161, GLY163, PHE164, TRP171, PRO181, [LEU38, TYR56, CYS184]
THR4, LEU8, ILE99,SER100, MET101, [GLN3, ILE5]
ASN1, ARG4, THR5, ILE6, LEU18, [SER2]
GLU11, TYR12, GLN56, HIS57, GLN61, TRP88, [ARG13, ASN14]
SER2, ARG4, THR5, ILE6, GLU14, [ASN1]
[GLU51, HIS57, GLN61], ALA64, ILE65, MET68, TRP88, ILE96, ALA97
[SER28, GLN39], LYS31, ARG32, PHE35, SER36, TYR38
1372-1
PE0415
LYS1, LEU61, ASP96, GLY99, VAL100, ASN151, ILE152, PRO154, ALA155, GLU156, TRP176, TYR159,
214-III
ARG22, THR45, GLN46, PHE49, THR47, ILE73, TYR52, [SER72]
4692-1
TYR39, LEU61, ASN93, ASN95, ASP96, GLY99, VAL100, TYR101, SER102, PRO105, VAL110, ILE152, HIS168
CYS9, SER10, TYR12, THR15, ILE17, THR19, ILE20, ASN21, THR6, GLU7, THR15, GLN16, ASN89, ASN90, THR92, [SER10] ASN14, TYR18, SER44, GLY45, GLU46, ASN89, ASN90, ASN94, SER26, TYR27, THR28, GLU29, THR41, GLY45, ARG73, LEU77
LEU18, SER19, TYR22, LEU23, TYR26, GLN27, VAL30, LYS31, PHE35, ILE21, ARG24, GLU25, SER28, PHE35, TYR38, GLN39, SER40
TYR26, GLN27, VAL30, LYS31, ILE34, PHE35, TYR38, GLN39, SER40, SER19, TYR22, LEU23, TYR26, GLN27, VAL30, ILE34, PHE35, TYR38
[LEU161], ILE36, ASN37, LEU38, TYR56, LEU113, ARG160, ALA162, GLY163, PHE164, TRP171, PRO181, CYS184
TYR27, THR28, SER30, MET31, [GLU29, ARG73]
ILE36, ASN37, TYR56, GLY163, PHE164, TRP171, PRO181, [LEU38, ARG160, LEU161, CYS184]
PHE35, TYR38, GLN39
HIS24, TYR27, PHE28, ARG30, GLN33, ILE36, GLY114, [THR32, ILE34]
LEU52, [TYR45, ILE48, ARG49, ASP50]
(Continued)
Analysis on subunits of heat labile enterotoxin of Escherichia coli Table 5.
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Serotype name
(Continued). Pentatriacontan-5-one A
B
4702-1
TYR39, TYR101, SER102, PRO103, PRO105, TYR106, [ARG43]
61A-4
ASN95, ASP96, GLY99, PRO105, TYR106, GLN108, PRO154, ALA155, GLU156, TYR159, THR87, ASP96, GLY99, VAL100, ASN151, ILE152, ALA155, TYR159, GLU173, GLU174, TRP176, ILE36, PRO89, LEU113, ASN151, ILE152, ALA153, PRO154, ASP157, LEU161
4321-1
PE0534
Table 6.
Proanthocyanidin C
A
B
THR10, CYS11, GLU14, THR15, LEU18, SER19, ILE21, TYR22, LYS25
PRO89, ASN149, LEU150, ILE152, ALA153, PRO154, [ASN151]
SER28, LYS31, ARG32, SER36, GLN39, [PHE35]
LYS14, GLY17, TYR27, PHE28, PRO117, TYR118, SER119, GLU141, [ARG30, THR32, MET34], HIS24, TYR27, PHE28, ASP29, GLN33
Energy values (kcal/mol) of three chains in different serotypes with the ligands.
Serotype name
Figure 13.
C
[ASP40], ASN37, TYR39, ARG43, GLY163, PHE164, PRO165,
Pentatriacontan-5-one
2781-5 PE0615 121-I 225-IV 1372-1 PE0415 214-III 4692-1 4702-1 61A-4 4321-1 PE0534
13
Proanthocyanidin
A
B
C
A
B
C
−.89 −1.54 −1.67 −2
−.34 −1.34 −1.7 −.36 −1.39 −.83
−.45 −2.29 .45 −2.97 −3.06 −.38 −0.83 −1.6 −3.02
−9.88 −15.09 −10.51 −10.46
−9.27 −9.14 −9.66 −9.34 −10.87 −10.73
−8.95 −8.06 −9.44 −7.7 −7.29 −8.31 −7.45 −8.25 −8.11
−1.74 −.29 −2.09 −2.2 −.44 −1.05 −2.79
−10.23 −11.17 −10.61 −8.24 −10.65 −9.5 −10.01
Molecular dynamics of chains A, B, and C (a, b, c) showing change in conformation at different time intervals.
14
M. Krishna Raja et al.
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Figure 14.
RMSD profile of different chains.
Acknowledgments The authors would like to acknowledge VIT University, Vellore for their constant support and facilities provided for doing excellence in research.
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